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How accurate is circular dichroism-based model validation?
Circular dichroism (CD) spectroscopy is highly sensitive to the secondary structure (SS) composition of proteins. Several methods exist to either estimate the SS composition of a protein or to validate existing structural models using its CD spectrum. The accuracy and precision of these methods depe...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456416/ https://www.ncbi.nlm.nih.gov/pubmed/32844286 http://dx.doi.org/10.1007/s00249-020-01457-6 |
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author | Nagy, Gabor Grubmüller, Helmut |
author_facet | Nagy, Gabor Grubmüller, Helmut |
author_sort | Nagy, Gabor |
collection | PubMed |
description | Circular dichroism (CD) spectroscopy is highly sensitive to the secondary structure (SS) composition of proteins. Several methods exist to either estimate the SS composition of a protein or to validate existing structural models using its CD spectrum. The accuracy and precision of these methods depend on the quality of both the measured CD spectrum and the used reference structure. Using a large reference protein set with high-quality CD spectra and synthetic data derived from this set, we quantified deviations from both ideal spectra and reference structures due to experimental limitations. We also determined the impact of these deviations on SS estimation, CD prediction, and SS validation methods of the SESCA analysis package. With regard to the CD spectra, our results suggest intensity scaling errors and non-SS contributions as the main causes of inaccuracies. These factors also can lead to overestimated model errors during validation. The errors of the used reference structures combine non-additively with errors caused by the CD spectrum, which increases the uncertainty of model validation. We have further shown that the effects of scaling errors in the CD spectrum can be nearly eliminated by appropriate re-scaling, and that the accuracy of model validation methods can be improved by accounting for typical non-SS contributions. These improvements have now been implemented within the SESCA package and are available at: https://www.mpibpc.mpg.de/sesca. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00249-020-01457-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7456416 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-74564162020-09-03 How accurate is circular dichroism-based model validation? Nagy, Gabor Grubmüller, Helmut Eur Biophys J Original Article Circular dichroism (CD) spectroscopy is highly sensitive to the secondary structure (SS) composition of proteins. Several methods exist to either estimate the SS composition of a protein or to validate existing structural models using its CD spectrum. The accuracy and precision of these methods depend on the quality of both the measured CD spectrum and the used reference structure. Using a large reference protein set with high-quality CD spectra and synthetic data derived from this set, we quantified deviations from both ideal spectra and reference structures due to experimental limitations. We also determined the impact of these deviations on SS estimation, CD prediction, and SS validation methods of the SESCA analysis package. With regard to the CD spectra, our results suggest intensity scaling errors and non-SS contributions as the main causes of inaccuracies. These factors also can lead to overestimated model errors during validation. The errors of the used reference structures combine non-additively with errors caused by the CD spectrum, which increases the uncertainty of model validation. We have further shown that the effects of scaling errors in the CD spectrum can be nearly eliminated by appropriate re-scaling, and that the accuracy of model validation methods can be improved by accounting for typical non-SS contributions. These improvements have now been implemented within the SESCA package and are available at: https://www.mpibpc.mpg.de/sesca. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00249-020-01457-6) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-08-26 2020 /pmc/articles/PMC7456416/ /pubmed/32844286 http://dx.doi.org/10.1007/s00249-020-01457-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Article Nagy, Gabor Grubmüller, Helmut How accurate is circular dichroism-based model validation? |
title | How accurate is circular dichroism-based model validation? |
title_full | How accurate is circular dichroism-based model validation? |
title_fullStr | How accurate is circular dichroism-based model validation? |
title_full_unstemmed | How accurate is circular dichroism-based model validation? |
title_short | How accurate is circular dichroism-based model validation? |
title_sort | how accurate is circular dichroism-based model validation? |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456416/ https://www.ncbi.nlm.nih.gov/pubmed/32844286 http://dx.doi.org/10.1007/s00249-020-01457-6 |
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